Shari would like to thank Soumendra Mohanty for his contribution to this month’s column.
Last month, I argued that the concept of business intelligence (BI) 2.0 promised much but without the right approach could fall at the first hurdle - effective data management. Once that hurdle is cleared, what should a company expect to see from a full BI 2.0 program, and what are the essential components required for BI 2.0 to be realized? The most talked-about impact stems from the fact that BI 2.0 is event driven and real time. The data generated is analyzed at the very moment the business event happens. This data is in the form of event streams, messages and alerts. This could include capital market transactions, claims registration, fraud detection and anti-money laundering, product shelf cycle time in larger supermarkets or other information enabling a vast range of business insights. With traditional BI solutions, there is typically a gap between knowing something and doing something about it at the very moment of the event happening, and largely this gap is attributed to “data latency.” While significant improvement on data latency is a much talked-about feature of BI 2.0, it also enables decision agility by being both individual data-centric and aggregate data-centric. By this I mean that while processing transactional data, BI 2.0 proposes to analyze each individual transactional data point against expected results at an aggregated level and provide automated alerts to take remedial actions.
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